小波分析-模糊聚类法用于滚动轴承故障诊断

Application of Wavelet Analysis-Cluster Fuzzy to Fault Diagnosis of Roller Bearings

为了对减速器内轴承的运行状态进行故障监测和诊断,在对振动加速度信号进行小波分析的基础上,提出了基于尺度-能量谱的特征提取和模糊聚类相结合的滚动轴承故障诊断方法。该方法应用于齿轮减速器JZQ250的故障诊断中,经对大量实测数据的处理和分析,能够比较准确地识别和诊断出减速器的正常运行状态、内圈故障和外圈故障运行状态,具有一定的工程实用价值。

This paper presents a method of fault diagnosis for roller bearings by using the scale-energy spectrum feature extraction and the fuzzy cluster analysis on the basis of the wavelet analysis of roller bearing vibration signals.Through processing and analyzing the massive measured data,the method can accurately identify and diagnose different running states of the JZQ250 gear-box,including the normal state,the inner ring and outer ring fault operation conditions.The results show that the method is of a certain value to engineering applications.